Understanding how physician cognitive biases affect the treatment of older adults with dementia and other vulnerable populations

项目摘要 Dan P.Ly，医学博士，国会议员，波士顿退伍军人事务部住院主治医师 他是哈佛大学卫生政策(经济学方向)的博士生，他长期- 长期利益在于提高对弱势群体的护理质量。这项博士后奖学金将对我们有所帮助。 李博士将发展成为一名独立的调查员，在医生决策方面拥有专业知识。李博士的范围很广 使用大型数据库的编程经验和他所接受的大量正式培训 为他进行拟议的研究做好准备。这项建议是关于医生之间的认知偏差 在照顾患有阿尔茨海默病和相关痴呆症(ADRD)的老年人时，可能会加剧 对于少数族裔患者，建立在李博士之前关于医疗保健差异的工作基础上，通过测试一种 这样的差距。培训计划将通过三个目标建立在先前培训的基础上：1)获得指导经验 在老年痴呆症和老年病专家的照顾下；2)培养帮助医生的专业知识 做出更好的决策；以及3)获得方法论技能(例如，定性方法和实验方法) 补充李博士在大型数据库分析方面的培训。李博士将由大卫·卡特勒博士指导，他是一名 全国知名的健康经济学家，是一位热心且经验丰富的导师。他的共同导师是阿努帕姆博士 耶拿是一位内科医生和健康经济学家，具有医生行为方面的专业知识。李博士已经收集了一份建议 由老年学、决策、统计、管理和信息学方面的专家组成的委员会。 众所周知，护理质量是次优的，特别是对老年人来说。随着人口老龄化，重要的是 确定向老年人提供高质量护理的障碍。一组障碍可能是医生的认知 在护理这类患者时可能更容易出现的偏见，特别是像ADRD这样的患者 这可能会使沟通变得困难。当关心种族和性别歧视时，一些认知偏差也可能恶化 少数民族患者。关于认知偏差在全国范围内对这些人造成的后果，人们知之甚少 脆弱人群，因为医生权衡的因素通常不在常用的索赔数据中。 李博士将使用来自退伍军人管理局的丰富的国家电子健康记录数据，并关注一个常见的场景： 评估呼吸急促患者发生肺栓塞(PE)的风险。他的项目有三个 目标。首先，他将检查医生是否注意到被确认为相关的客观临床因素。 以及他们是否也关注有争议的外部因素，如最近患者的诊断 已见(目标1)。其次，他将确定医生对这些客观因素的关注是否显著 ADRD患者较低(目标2)。第三，他将研究这种关注度是否也显著低于 少数族裔患者(目标3)。这项研究可能有助于解释弱势群体在护理质量上的不足。 并为未来干预措施的设计提供信息，以对抗认知偏见和改善护理。

Project Summary Dan P. Ly, MD, MPP, is an inpatient teaching attending physician in the Veterans Affairs (VA) Boston Healthcare System and a PhD candidate in health policy (economics track) at Harvard University whose long- term interest is in improving the quality of care for vulnerable populations. This postdoctoral fellowship will help Dr. Ly develop into an independent investigator with expertise in physician decision-making. Dr. Ly's extensive programming experience with large databases and the substantial formal training he has received have prepared him to perform the proposed research. This proposal, on how cognitive biases among physicians may be exacerbated when caring for older adults with Alzheimer's Disease and Related Dementias (ADRD) and for minority patients, builds on Dr. Ly's prior work on health care disparities by testing for a mechanism for such disparities. The training plan will build upon prior training through three goals: 1) gain guided experience with the care of older adults from specialists in dementia and geriatrics; 2) develop expertise in helping doctors make better decisions; and 3) acquire skills in methodology (e.g., qualitative and experimental methods) complementary to Dr. Ly's training in large database analysis. Dr. Ly will be mentored by Dr. David Cutler, a nationally-renowned health economist who is an eager and experienced mentor. His co-mentor is Dr. Anupam Jena, a physician and health economist with physician behavior expertise. Dr. Ly has assembled an advisory committee with expertises in gerontology, decision-making, statistics, management, and informatics. Quality of care is known to be suboptimal, particularly for older adults. As the population ages, it is important to identify barriers to delivering high-quality care to older adults. One set of barriers may be physician cognitive biases that may occur more often when caring for such patients, especially patients with conditions like ADRD that may make communication difficult. Some cognitive biases may also worsen when caring for racial and ethnic minority patients. Little is known about consequences of cognitive biases on a national scale for these vulnerable populations because the factors physicians weigh are often not in the claims data commonly used. Dr. Ly will use rich, national electronic health record data from the VA and focus on a common scenario: assessing patients with shortness of breath for the risk of pulmonary embolism (PE). His project has three aims. First, he will examine whether physicians pay attention to objective clinical factors validated to correlate with PE risk and whether they also focus on arguably extraneous factors, such as diagnoses of recent patients seen (Aim 1). Second, he will determine whether physician attention on these objective factors is significantly lower for patients with ADRD (Aim 2). Third, he will examine whether this attention is also significantly lower for minority patients (Aim 3). This research may help explain deficiencies in quality of care for vulnerable populations and inform the design of future interventions to counter cognitive biases and improve care.